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Meet
NuPlay AI's enterprise AI models are purpose-built for conversational intelligence, reasoning, and high-volume execution.
<600ms
end-to-end voice latency, in production
Zero
third-party model dependencies
100%
self-hosted, your infrastructure
Our Models
A reasoning LLM and a fast, fine-tuned SLM, self-hosted and tuned on your own conversations.
Astra LLM
NuPlay AI's in-house LLM, built for complex, high-reasoning enterprise voice conversations. Tuned continuously on production data, with zero dependency on third-party model providers.
Astra SLM
An 9B specialist model, fine-tuned per domain, built for real-time, high-volume voice and chat. Deployable inside your own VPC, and tuned continuously on your own production calls.
Three things that change with Astra
Calls that don't feel robotic or laggy
Built for time-to-first-token, delivering sub-1-second voice latency in production, not just the lab.
Built for complete data control
Self-hosted with no shared LLMs. Your conversations stay private, secure, and fully under your control.
Lower AI costs at scale
A smaller, more efficient model lowers the cost of every completed customer conversation.
Your voice agent has a silent owner
Access can change overnight
A provider updates terms, revokes a model version, or re-prioritizes capacity, and your production agents inherit the outage. You didn't choose the timing.
Access can change overnight
Token-based pricing means your cost grows exactly as your usage grows. There's no version of success that doesn't also increase the bill per conversation.
Your data trains someone else's model
Every production call is a tuning signal. On a third-party model, that signal benefits the provider's roadmap, not the system you're actually running.
Full-stack ownership isn't a feature.
It's a different category.
Owns the model
Self-hosted infrastructure
Exposed to third-party access changes
Tuned on your production data
Cost model
Platform assemblers
Full-stack, model-dependent
by NUPLAY AI
Astra isn't a model you plug in. It's the centre of a system built to run voice agents in production
A token-efficient language layer built for LLM-native use.
Continuous quality control for voice agents in production.
Define, test, and refine agent behavior.
